Upgrading Fitness in the Production of Garments

Abstract

This article uses a series of data mining techniques to analyze body types and introduce a new sizing chart in order to produce garments for males. A principle component analysis and hierarchical and non-hierarchical clustering approaches are used to form a new sizing chart. All variables are grouped into two main components with a principle component analysis. Agglomerative hierarchical clustering is used to determine the number of clusters, and then a k-means algorithm is applied to segment the heterogonous population to actually form the clusters. The resultant innovations in designing garments have improved both non-price and price factors, the fittings of garments on all bodies have effectively improved and fabric waste has decreased, so the main goals which include improvement in quality with more comfort and a lower price have been met.

Publication Title

Research Journal of Textile and Apparel

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